Freeplay is a platform for building and improving AI products using evaluations, experiments, observability, and data review workflows tailored for enterprise teams.
Freeplay is an AI product development platform designed to help teams systematically build, evaluate, and improve AI applications and agents. It centralizes experimentation, evaluation, and data workflows so teams can move beyond ad-hoc prompts and manual testing toward a repeatable, data-driven process. The primary purpose of Freeplay is to create a continuous improvement loop (βdata flywheelβ) that connects real user interactions back into model quality and product performance.
Core capabilities include structured evaluations (both automated and human-in-the-loop) to measure model quality across scenarios, regression testing to catch quality drops, and experiment management to compare prompts, models, and configurations. Freeplay provides observability features such as tracing, logging, and analytics to understand how AI systems behave in production, including failure modes and edge cases. It also supports data review workflows, enabling teams to label, curate, and prioritize real-world examples for fine-tuning, prompt refinement, or policy updates. Integration with existing infrastructure and tools allows teams to adopt Freeplay incrementally without disrupting current pipelines.
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